Software engineer and data scientist with diverse background currently working on PhD in Natural Language Processing (NLP). Focused on applying machine learning techniques to biomedical text data. http://www.wbriggs.co.uk/ EDUCATION: University of Sheffield, PhD in Biomedical NLP, (October 2017 – Present) • Research and applied driven PhD on developing Natural Language Processing and Machine Learning techniques to handle large volumes of medical literature data. Emphasis on cost-effectiveness for systematic review decision makers and automation of complex queries to reduce the overall overhead of the entire systematic review process. • Used Apache Lucene to build an efficient index of entire PubMed database along with applying stop-word removal, stemming, normalization and n-gram modeling. Provided a suitable client-server query interface for retrieving relevant medical documents. Submitted a technical paper to the CLEF 2018 healthcare conference on using RAKE keyword extraction algorithm to identify important information from systematic review summaries. • Implemented a Gaussian Process with scikit-learn and applied data sampling to model occurrences of relevant documents for queries and make predictions of how many relevant documents are likely to be present an entire data set. Evaluated existing approaches to cost-effectiveness problem and presented a novel approach using new methods. University of Sheffield, MSc in Advanced Computer Science (Distinction), (2017) • Dissertation Project: Affect analysis for social media. Scraped Twitter and used unsupervised learning technique to build data set. Performed sentiment/affect classification using various algorithms: Naive Bayes, SVM and Random Forest. Used libraries such as scikit-learn, Keras and TensorFlow. Formally evaluated against state-of-the-art systems. Implemented two neural networks, LSTM and CNN. Built working demo using AWS EC2. Applied gensim word2vec word embeddings. • Text Processing: Developed an Information Retrieval (IR) engine using tf-idf weighting scheme and vector space model. Implemented Rocchio relevance feedback algorithm to extend performance. Evaluated using formal metrics (F-measure, recall and precision). Generated probabilistic statistical alignments for machine translation by programmatically analysing a parallel corpus using both expectation maximization (EM) algorithm and IBM models. • Cloud Computing and Intelligent Web: Developed a platform as a service (PaaS) using Java servlets, jsp, html and JavaScript. Provided an interface for other developers to upload their own apps on the platform. Used Node.js to develop a server for processing large volumes of Twitter data. Developed a front-end interface for client querying of pre-processed Twitter data using W3 CSS, Ajax and Socket IO. • IOS Development: Worked on two major applications with strong emphasis on design principles including MVC, strategy, factory and template method design patterns. Provided a universal app interface for support across a range of iOS devices. Worked on a sentiment analysis focused project which extracted public emotions from social media data. Used Twitter API and a Naive Bayes classifier to dynamically assess sentiment of surrounding local area. University of Derby, BSc in Computer Science (2:1), (2014) WORK EXPERIENCE: October 2017 – Present University of Sheffield – Academic Demonstrator • Teaching undergraduate students computer programming in Java and Python. • Supervising group work between students. Marking assignments, providing oral and written feedback. • Introducing NLP concept to students through Information retrieval, weighting schemes, feature selection, pre-processing, tokenisation, sentiment analysis and regular expressions. September 2014 – March 2016 Tribal Group – Developer • Developed dynamic WPF / C# based educational software with database support of both SQL Server and Oracle. • Contributed to bug fixing, new development features, optimisation of existing code, unit testing, profiling using ANTS. • Key role in engineering a new module for Australian colleges data returns using multi-threaded design principles, task scheduling across projects and rich, intuitive user interfaces with progress reporting. Fully unit tested implementation. • Agile/Scrum software development methodology. Took part in daily stand-ups. Undertook role of scrum master for a series of sprints. TECHNICAL SKILLS: • Programming languages: C#, Python, C, C++, Java, Cuda, x86 assembly, HTML, JavaScript, PHP • Web Technologies: Ajax, Socket IO, Node.js, jQuery, HTML5, CSS, JSP, AWS (EC2, S3, Aurora) • IDEs: Spyder, Eclipse, Visual Studio, Codeblocks • Frameworks: scikit-learn, Keras, iOS, .NET, nltk, gensim, GATE, WPF, ASP.net, pandas, NumPy • Source Control: TFS, Git • Patterns, Design Principles: SOLID, GOF, MVVM, MVC • Databases: MySQL, Oracle SQL, SQL Server, SQLite